Tze Leung Lai, Philip W Lavori, Mei-Chiung I Shih, Branimir I Sikic. Published in Clinical trials, vol. 9, no. 2, 141-154, 2012.
Description
Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations. We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature.
Software
An R package for running the simulations in the paper is available. There is additional work that needs to be done to make this a more general package than it is currently. We have versions for Unix, Macintosh and Windows.
On Unix, open up a terminal and type
R CMD INSTALL bgct_1.01.tar.gz
On a Mac, open up a terminal and type
R CMD INSTALL bgct_1.01.tgz
On Windows, using the Package menu, choose Install from local zip files and navigate to the downloaded zip file.
Once installed,
use library(bgct)
example(runOvarianTrial)
to run 10 simulations of the scenarios in the paper.